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Correlation between visit-to-visit and short-term blood pressure variability calculated using different methods and glomerular filtration rate

Journal of Human Hypertension volume 31, pages 132–137 (2017)Cite this article

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Abstract

The aim of this study was to explore the correlation between visit-to-visit and short-term blood pressure variability (BPV), including systolic BPV (SBPV) and diastolic BPV (DBPV), calculated using different methods, and the glomerular filtration rate (GFR) in a late, middle-aged population. Using cluster sampling, we randomly selected retired employees of the Kailuan Group who were ⩾60 years and participated in a third health examination for 24-h ambulatory blood pressure monitoring and inspection. Among the 3064 randomly selected observation subjects, 2464 were included based on the criteria. BPV was calculated using s.d., coefficient of variation (CV, s.d./Mean), variability independent of mean (VIM, s.d./Meanx) and BPV ratio (BPVR, s.d. (SBPV)/s.d. (DBPV)). Multivariate linear regression was used to analyse the correlation between estimated GFR (eGFR) and BPV calculated using different methods. The mean age of 2464 subjects was 67.4±6.1 years, with 1667 male subjects (67.7%). A total of 2104 cases were included in the visit-to-visit BPV group, and 1382 in the short-term BPV group. SBPV calculated using different methods showed statistically significant increasing trends for the SBP versus all s.d. and short-term BPVR. There was a significant, positive correlation between the visit-to-visit and short-term BPV calculated using different methods, which were all negatively correlated with eGFR (P<0.05). Multivariate linear regression analysis showed that, with correction for possible confounding factors, SBPV (24-h s.d., CV and VIM, and daytime CV and night time CV) and all DBPV demonstrated negative linear relationships with eGFR (P<0.05).

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References

  1. Muntner P, Shimbo D, Tonelli M, Reynolds K, Arnett DK, Oparil S . The relationship between annual variability in systolic blood pressure and all-cause mortality in the general population: findings from NHANES III, 1988–1994. Hypertension 2011; 57 (2): 160–166.

    Article  CAS  Google Scholar 

  2. Rothwell PM, Howard SC, Dolan E, O’Brien E, Dobson JE, Dahlöf B et al. Prognostic significance of annual variability, maximum systolic blood pressure, and episodic hypertension. Lancet 2010; 375 (9718): 895–905.

    Article  Google Scholar 

  3. Gavish B, Ben-Dov IZ, Kark JD, Mekler J, Bursztyn M . The association of a simple blood pressure-independent parameter derived from ambulatory blood pressure variability with short-term mortality. Hypertens Res 2009; 32 (6): 488–495.

    Article  Google Scholar 

  4. Veerman DP, de Blok K, vnn Montfrans A . Relationship of steady state and ambulatory blood pressure variability to left ventricular mass and urinary albumin excretion in essential hypertension. Am J Hypertens 1996; 9 (5): 455–460.

    Article  CAS  Google Scholar 

  5. Manios E, Tsagalis G, Tsivgoulis G, Barlas G, Koroboki E, Michas F et al. Time rate of blood pressure variation is associated with impaired renal function in hypertensive patients. J Hypertens 2009; 27 (11): 2244–2248.

    Article  CAS  Google Scholar 

  6. Wu SL, Huang ZR, Yang XC, Zhou Y, Wang AX, Chen L et al. Prevalence of ideal cardiovascular health and its relationship with the 4-year cardiovascular events in a northern Chinese industrial city. Circ Cardiovasc Qual Outcomes 2012; 5 (4): 487–493.

    Article  Google Scholar 

  7. Farhan H, Al M . Comparative study of ambulatory blood pressure monitoring and clinic blood pressure measurement in the risk assessment and management of hypertension. Sultan Qaboos Univ Med J 2010; 10 (3): 370–376.

    PubMed  PubMed Central  Google Scholar 

  8. Su C, Zhang GX, Wang RF, Yuan L, Zhang JJ, Wang XR et al. Application of the CKD-EPI equation for estimation of glomerular filtration rate in Chinese patients with chronic kidney disease. Chin J Dis Control Prev 2013; 17 (7): 621–624.

    CAS  Google Scholar 

  9. Okada H, Fukui M, Tanaka M, Inada S, Mineoka Y, Nakanishi N et al. Annual variability in systolic blood pressure is correlated with diabetic nephropathy and atherosclerosis in patients with type 2 diabetes. Atherosclerosis 2012; 220 (1): 155–159.

    Article  CAS  Google Scholar 

  10. Hata J, Arima H, Rothwell PM, Woodward M, Zounqas S, Anderson C et al. Effects of annual variability in systolic blood pressure on macrovascular and microvascular complications in patients with type 2 diabetes mellitus: the ADVANCE trial. Circulation 2013; 128 (12): 1325–1334.

    Article  Google Scholar 

  11. Kawai T, Ohishi M, Kamide K, Nakama C, Onishi M, Ito N et al. Differences between daytime and nighttime blood pressure variability regarding systemic atherosclerotic change and renal function. Hypertens Res 2013; 36 (3): 232–239.

    Article  Google Scholar 

  12. Narkiewicz K, Winnicki M, Schroeder K, Phillips BG, Kato M, Cwalina E et al. Relationship between muscle sympathetic nerve activity and diurnal blood pressure profile. Hypertension 2002; 39 (1): 168–172.

    Article  Google Scholar 

  13. Kawai T, Ohishi M, Ito N, Onishi M, Takeya Y, Yamamoto K et al. Alteration of vascular function is an important factor in the correlation between annual blood pressure variability and cardiovascular disease. J Hypertens 2013; 31 (7): 1387–1395.

    Article  CAS  Google Scholar 

  14. Yokota K, Fukuda M, Matsui Y, Hoshide S, Shimada K, Kario K . Impact of annual variability of blood pressure on deterioration of renal function in patients with nondiabetic chronic kidney disease. Hypertens Res 2013; 36 (2): 151–157.

    Article  CAS  Google Scholar 

  15. Grassi G, Quarti-Trevano F, Seravalle G, Arenare F, Volpe M, Furiani S et al. Early sympathetic activation in the initial clinical stages of chronic renal failure. Hypertension 2011; 57 (4): 846–851.

    Article  CAS  Google Scholar 

  16. Su DF, Miao CY . Blood pressure variability and organ damage. Clin Exp Pharmacol Physiol 2001; 28 (9): 709–715.

    Article  CAS  Google Scholar 

  17. Mancia G, Fagard R, Narkiewicz K, Redon J, Zanchetti A, Böhm M et al. ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J 2013; 34 (28): 2159–2219.

    Article  Google Scholar 

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Acknowledgements

We thank all participants and staff of the Kailuan study for their important contributions.

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Authors and Affiliations

  1. Medical Informatics Center, Peking University, Beijing, People’s Republic of China

    J Wang

  2. Department of Orthopedics and Trauma, Peking University People’s Hospital, Beijing, People’s Republic of China

    B Jiang

  3. North China University of Science and Technology, Tangshan, People’s Republic of China

    L Song

  4. Department of Epidemiology and Biostatistics, Peking University, Beijing, People’s Republic of China

    C Yang

  5. Department of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, People’s Republic of China

    Y Wu, S Chen, C Li, H Zhao & S Wu

  6. Sixth Hospital of Peking University, Beijing, People’s Republic of China

    F Wang

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  1. J Wang
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Correspondence to F Wang or S Wu.

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Supplementary Information accompanies this paper on the Journal of Human Hypertension website

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Wang, J., Jiang, B., Song, L. et al. Correlation between visit-to-visit and short-term blood pressure variability calculated using different methods and glomerular filtration rate. J Hum Hypertens 31, 132–137 (2017). https://doi.org/10.1038/jhh.2016.51

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  • DOI: https://doi.org/10.1038/jhh.2016.51

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